Traditional fuzzy logic systems are unable to handle the uncertainties of real-world applications. By "handle" I mean directly model and minimize the effect of. In this talk I will explain rule-based type-2 fuzzy logic systems and how they can handle a broad range of uncertainties totally within their framework. This is accomplished by adding a new mathematical dimension-a third dimension-to ty...

In this contribution we carry out an analysis of the rule weights and Fuzzy Reasoning Methods for Fuzzy Rule Based Classification Systems in the framework of imbalanced data-sets with a high imbalance degree. We analyze the behaviour of the Fuzzy Rule Based Classification Systems searching for the best configuration of rule weight and Fuzzy Reasoning Method also studying the cooperation of some...

This paper reveals the analytical structure of a fuzzy twoterm (PI/PD) controller which employs N1 (≥3) number of symmetric fuzzy sets for the input variable ‘displacement’, N2 (≥3) number of symmetric fuzzy sets for the input variable ‘velocity’ and N1+N2-1 number of symmetric fuzzy sets for the output variable ‘controller output’. The analytical structures are derived via triangular membershi...

To make full use of the polarization information electromagnetic waves for polarimetric sensor array, we derive orthogonality expression state based on Poincaré sphere (PS) representation. The ellipticity angle and orientation ellipse are used to describe point surface sphere. derivation shows that two points characterize a pair orthogonal states distributed in opposite positions. Compared with...

Problem statement: We present development of neural network based fuzzy inference system for scheduling of parallel Jobs with the help of a real life workload data. The performance evaluation of a parallel system mainly depends on how the processes are co scheduled? Various co scheduling techniques available are First Come First Served, Gang Scheduling, Flexible Co Scheduling and Agile Algorith...